Learned Models:
We consider two types of learned models: GAMs and sparse neural networks.
The former was introduced as a rich but simple model: capable of modeling nonlinear effects while conducive for understanding feature significance [1]}. Each \(f_j(\cdot )\)  is a smooth nonparametric function that is fit using splines. A link function relates the summation of each \(f_j(\cdot )\)  to the target response, such as the identity link for regression and the logit link for classification.
